Package: beyondWhittle 1.3.0
Renate Meyer
beyondWhittle: Bayesian Spectral Inference for Time Series
Implementations of Bayesian parametric, nonparametric and semiparametric procedures for univariate and multivariate time series. The package is based on the methods presented in C. Kirch et al (2018) <doi:10.1214/18-BA1126>, A. Meier (2018) <https://opendata.uni-halle.de//handle/1981185920/13470> and Y. Tang et al (2023) <doi:10.48550/arXiv.2303.11561>. It was supported by DFG grants KI 1443/3-1 and KI 1443/3-2.
Authors:
beyondWhittle_1.3.0.tar.gz
beyondWhittle_1.3.0.tar.gz(r-4.5-noble)beyondWhittle_1.3.0.tar.gz(r-4.4-noble)
beyondWhittle_1.3.0.tgz(r-4.4-emscripten)beyondWhittle_1.3.0.tgz(r-4.3-emscripten)
beyondWhittle.pdf |beyondWhittle.html✨
beyondWhittle/json (API)
# Install 'beyondWhittle' in R: |
install.packages('beyondWhittle', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 8 days agofrom:bbdf52ae70. Checks:OK: 2. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 25 2024 |
R-4.5-linux-x86_64 | OK | Nov 25 2024 |
Exports:bayes_factorbdp_dw_bayes_factor_k1bdp_dw_est_post_statsbdp_dw_mcmc_params_genbdp_dw_prior_params_genfourier_freqgibbs_argibbs_bdp_dwgibbs_npgibbs_npcgibbs_vargibbs_vnplocal_moving_FT_zigzagpacf_to_arpsd_armapsd_tvarma12psd_varmarmvnormscree_type_arsim_tvarma12sim_varma
Dependencies:BHclicolorspacecurlfansifarverforecastfracdiffgenericsggplot2gluegtableisobandjsonlitelabelinglatticelifecyclelmtestltsamagrittrMASSMatrixmgcvmunsellnlmennetpillarpkgconfigquadprogquantmodR6RColorBrewerRcppRcppArmadillorlangscalestibbletimeDatetseriesTTRurcautf8vctrsviridisLitewithrxtszoo